Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution
1
Ministry of Education Key Laboratory for Earth System modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
2
Department of Land, Air, and Water Resources, University of California, Davis, CA 95616, USA
3
Tsinghua Urban Institute, Tsinghua University, Beijing 100084, China
4
Center for Healthy Cities, Institute for China Sustainable Urbanization, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(12), 1922; https://doi.org/10.3390/rs12121922
Received: 8 May 2020 / Revised: 6 June 2020 / Accepted: 11 June 2020 / Published: 14 June 2020
(This article belongs to the Special Issue Urban Land Use Mapping and Analysis in the Big Data Era)
Nighttime light remote sensing has aroused great popularity because of its advantage in estimating socioeconomic indicators and quantifying human activities in response to the changing world. Despite many advances that have been made in method development and implementation of nighttime light remote sensing over the past decades, limited studies have dived into answering the question: Where does nighttime light come from? This hinders our capability of identifying specific sources of nighttime light in urbanized regions. Addressing this shortcoming, here we proposed a parcel-oriented temporal linear unmixing method (POTLUM) to identify specific nighttime light sources with the integration of land use data. Ratio of root mean square error was used as the measure to assess the unmixing accuracy, and parcel purity index and source sufficiency index were proposed to attribute unmixing errors. Using the Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light dataset from the Suomi National Polar-Orbiting Partnership (NPP) satellite and the newly released Essential Urban Land Use Categories in China (EULUC-China) product, we applied the proposed method and conducted experiments in two China cities with different sizes, Shanghai and Quzhou. Results of the POTLUM showed its relatively robust applicability of detecting specific nighttime light sources, achieving an rRMSE of 3.38% and 1.04% in Shanghai and Quzhou, respectively. The major unmixing errors resulted from using impure land parcels as endmembers (i.e., parcel purity index for Shanghai and Quzhou: 54.48%, 64.09%, respectively), but it also showed that predefined light sources are sufficient (i.e., source sufficiency index for Shanghai and Quzhou: 96.53%, 99.55%, respectively). The method presented in this study makes it possible to identify specific sources of nighttime light and is expected to enrich the estimation of structural socioeconomic indicators, as well as better support various applications in urban planning and management.
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Keywords:
NPP-VIIRS; EULUC; temporal linear unmixing; urban
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MDPI and ACS Style
Ren, Z.; Liu, Y.; Chen, B.; Xu, B. Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution. Remote Sens. 2020, 12, 1922. https://doi.org/10.3390/rs12121922
AMA Style
Ren Z, Liu Y, Chen B, Xu B. Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution. Remote Sensing. 2020; 12(12):1922. https://doi.org/10.3390/rs12121922
Chicago/Turabian StyleRen, Zhehao; Liu, Yufu; Chen, Bin; Xu, Bing. 2020. "Where Does Nighttime Light Come From? Insights from Source Detection and Error Attribution" Remote Sens. 12, no. 12: 1922. https://doi.org/10.3390/rs12121922
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